Deterministic Insight into ANN Model Performance for Storm Runoff Simulation

The artificial neural network (ANN) theory has been widely applied to practical applications in hydrology. Since watershed rainfall–runoff processes are nonlinear and exhibit spatial and temporal variability, the ANN model, which considers watershed nonlinear characteristics, can usually but not always obtain satisfactory simulation results. The training of an ANN network is based completely on the reliability of the available hydrologic records. The objective of this study was to provide deterministic insight into the limitations of storm runoff simulation when using ANN. Hydrologic records of 42 storm events from two watersheds in Taiwan were adopted for analysis. A deterministic runoff model was used to classify the hydrologic records into “usual” and “unusual” storm events. The analytical results show that the ANN model could provide good simulation results for “usual” storm events; however, its performance was poor when it was applied to “unusual” storm events because no consistent hydrologic characteristics could be extracted from the storm event records using ANN. The success of the ANN model in usual storm discharge simulations may be mainly due to the input vectors including the previous observed discharge. Moreover, the number of past periods of rainfall that were set as the input vectors of the ANN model was found to be highly correlated with the watershed time of concentration. It can be used to efficiently determine the ANN network structure instead of using iterative network training.     

Comparing phenanthrene degradation by alginate‐encapsulated and free Pseudomonas sp. UG14Lr cells in heavy metal contaminated soils

BACKGROUND: Many polycyclic aromatic hydrocarbon (PAH) contaminated sites also contain high levels of toxic heavy metals. The presence of heavy metals can adversely affect PAH biodegradation. Encapsulation of bacterial cells has been shown to improve survival and activity of cells under various environmental stresses. This study examined if encapsulation of a phenanthrene‐mineralizing bacterial strain could improve its survival and phenanthrene degradation in heavy metal contaminated soils. RESULTS: Alginate encapsulation did not improve survival and phenanthrene degradation by Pseudomonas sp. UG14Lr in heavy metal contaminated soil. Phenanthrene degradation by, and survival of, free cells and alginate‐encapsulated cells were similar in soil contaminated with 5 mg kg^?1 dry soil of As, Cd, or Pb. The number of UG14Lr cells decreased to undetectable level when the concentration of each heavy metal was increased to 100 mg kg^?1 dry soil. UG14Lr, when inoculated as free cells, survived the best and they were detected over 60 days of incubation in soil. Cells in both wet and dry alginate beads survived less well than free cells at the higher metal concentrations. Correspondingly, phenanthrene degradation in soil inoculated with free UG14Lr was better than that in soil inoculated with alginate‐encapsulated cells. CONCLUSION: Alginate encapsulation adversely affected the survival and phenanthrene degradation ability of UG14Lr cells in heavy metal contaminated soil. It is postulated that alginate may have concentrated the metals which in turn increased the toxicity to UG14Lr cells. The results are of interest to those interested in the use of encapsulation technology to formulate microbial cells for bioremediation purposes. Copyright © 2009 Society of Chemical Industry     

Effects of Hexasulfobutylated C60 on the Thalamic Neurons in Neonatal Rat in vitro

The effects of hexasulfobutylated C₆₀ (FC₄S) on membrane potentials and currents were studied by tight-seal, whole-cell recording in thin slices of the neonatal rat thalamus. Silent neuron with resting membrane potentials of around -62.4 ± 0.7 mV was found in whole-cell current clamp recordings. Hexasulfobutylated C₆₀ depolarized the neuron by a concentration dependent manner. It also (1) prolonged the decay time constant of action potential and (2) decreased the threshold of the directly elicited action potentials of the neuron. Hexasulfobutylated C₆₀ did not alter the input resistance of the excitable membrane. In whole-cell voltage clamp studies, depolarizing command pulses from a holding potential of about -70 mV evoked a fast inward current followed by an outward current in the thalamic neurons. Hexasulfobutylated C₆₀ (30 - 100 μM) increased the total inward sodium current of the neuron, while hexasulfobutylated C₆₀ did not alter the outward potassium currents in all voltage steps tested. It was concluded that hexasulfobutylated C₆₀ (1) decreased the threshold of the action potential and (2) prolonged the decay time constant of the directly elicited action potential of the neonatal rat thalamic neurons. The effect may be closely associated with the Na⁺ current in thalamic neurons.     

Flocculation and sedimentation of cane sugar juice particles with cationic homo‐ and copolymers

Rapid flocculation and sedimentation of suspended particles in primary cane sugar juice is achieved using a high molecular weight anionic polymer flocculant. This work reports on efforts to enhance the performance of an anionic flocculant by the addition of cationic polymers. Homopolymers of poly(trimethylammonium ethyl methacrylate chloride) (TMAEMAC) and cationic copolymers of poly(trimethylammonium ethyl acrylate chloride) (TMAEAC) and acrylamide were synthesized and their performance, to enhance the flocculation and sedimentation of cane sugar juice particles, was evaluated by turbidity and settling rate measurements. The charge–patch mechanism best explains the performance of the homopolymers, whereas the action of the copolymers is attributed to the bridging mechanism. The results of this work indicate that the copolymers are more effective than the homopolymers to aid flocculation and sedimentation of the cane sugar juice particles, and that the best‐performing polymers are those that act by the bridging mechanism. Addition of increased amounts of anionic flocculant did not confer an improvement, suggesting that the cationic bridging flocculant targets a different population of particles that is largely responsible for the residual turbidity. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 316–325, 2003     

The temperature dependence of the doolittle equation parameter for polymer liquids

The Doolittle equation parameter for polymer liquids is a function of temperature. Its dependence on temperature can be expressed by a quadratic equation. The constants in the equation are determined for four vinyl-type polymer liquids: polystyrene (PS), poly(vinyl acetate) (PVAc), polydimethylsiloxane (PDMS), and polyisobutylene (PIB). It was found that the Doolittle parameter decreases with increasing temperature. Equations are presented for the pressure and temperature coefficients of viscosity, isoviscous temperature coefficient of volume, and the constant K_m in the Miller equation. Comparisons of the predictions of the equations, with those in the literature, are favorable. © 1993 John Wiley & Sons, Inc.     

On the application and design of artificial neural networks formotor fault detection. I

The general design considerations for feedforward artificial neural networks (ANNs) to perform motor fault detection are presented. A few noninvasive fault detection techniques are discussed, including the parameter estimation approach, human expert approach, and ANN approach. A brief overview of feedforward nets and the backpropagation training algorithm, along with its pseudocodes, is given. Some of the neural network design considerations such as network performance, network implementation, size of training data set, assignment of training parameter values, and stopping criteria are discussed. A fuzzy logic approach to configuring the network structure is presented     

Spectral Domain Analysis of Coaxial Cavities

Coaxial cavities are used in high power gyrotrons as the beam-wave interaction structure. Much research has been devoted to their mode selective properties. A coaxial cavity lacks a sharp boundary at its open end, so it has some physical features that can only be observed using a spectral model, such as frequency-dependent field profiles and mode overlapping effects. These properties are important since cold tests are usually conducted in the frequency domain. This study applies the incident/reflected wave boundary condition to the wave equation of a weakly irregular coaxial waveguide. The resistivity of the wall is considered in the analysis. Calculations reveal that the fixed-position spectrum yields an uncertain resonant frequency and quality factor. Although the maximum-field spectrum can uniquely determine the properties of the coaxial cavity, the resonant frequency obtained using the maximum-field spectral model is inconsistent with that obtained using the temporal model. The field-energy spectrum explains the low Q nature of the coaxial cavity. Moreover, resonant frequencies evaluated using the field-energy spectrum agree precisely with those evaluated using the temporal model.     

On modeling of if-then rules for probabilistic inference

We identify various situations in probabilistic intelligent systems in which conditionals (rules) as mathematical entities as well as their conditional logic operations are needed. In discussing Bayesian updating procedure and belief function construction, we provide a new method for modeling if… then rules as Boolean elements, and yet, compatible with conditional probability quantifications. © 1994 John Wiley & Sons, Inc.